An active learning reliability method combining Kriging constructed with exploration and exploitation of failure region and subset simulation
• A new reliability method combining Kriging and subset simulation is proposed. • Kriging is constructed based on exploration and exploitation of failure region. • Error measure functions are defined to quantify Kriging metamodel error. • The proposed method can handle problems with small failure pr...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zhang, Jinhao [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Umfang: |
13 |
|---|
| Übergeordnetes Werk: |
Enthalten in: Partial rescue of some features of Huntington Disease in the genetic absence of caspase-6 in YAC128 mice - Wong, Bibiana K.Y. ELSEVIER, 2015, London [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:188 ; year:2019 ; pages:90-102 ; extent:13 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.ress.2019.03.002 |
|---|
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ELV046711716 |
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| 520 | |a • A new reliability method combining Kriging and subset simulation is proposed. • Kriging is constructed based on exploration and exploitation of failure region. • Error measure functions are defined to quantify Kriging metamodel error. • The proposed method can handle problems with small failure probabilities. • Results of seven examples verify the accuracy and efficiency of proposed method. | ||
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10.1016/j.ress.2019.03.002 doi GBV00000000000616.pica (DE-627)ELV046711716 (ELSEVIER)S0951-8320(18)30932-3 DE-627 ger DE-627 rakwb eng 540 610 VZ 15,3 ssgn PHARM DE-84 fid 44.40 bkl 58.28 bkl Zhang, Jinhao verfasserin aut An active learning reliability method combining Kriging constructed with exploration and exploitation of failure region and subset simulation 2019 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • A new reliability method combining Kriging and subset simulation is proposed. • Kriging is constructed based on exploration and exploitation of failure region. • Error measure functions are defined to quantify Kriging metamodel error. • The proposed method can handle problems with small failure probabilities. • Results of seven examples verify the accuracy and efficiency of proposed method. Xiao, Mi oth Gao, Liang oth Enthalten in Elsevier Science Wong, Bibiana K.Y. ELSEVIER Partial rescue of some features of Huntington Disease in the genetic absence of caspase-6 in YAC128 mice 2015 London [u.a.] (DE-627)ELV018738095 volume:188 year:2019 pages:90-102 extent:13 https://doi.org/10.1016/j.ress.2019.03.002 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-PHARM SSG-OLC-PHA SSG-OPC-PHA GBV_ILN_32 GBV_ILN_40 GBV_ILN_62 44.40 Pharmazie Pharmazeutika VZ 58.28 Pharmazeutische Technologie VZ AR 188 2019 90-102 13 |
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An active learning reliability method combining Kriging constructed with exploration and exploitation of failure region and subset simulation |
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• A new reliability method combining Kriging and subset simulation is proposed. • Kriging is constructed based on exploration and exploitation of failure region. • Error measure functions are defined to quantify Kriging metamodel error. • The proposed method can handle problems with small failure probabilities. • Results of seven examples verify the accuracy and efficiency of proposed method. |
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• A new reliability method combining Kriging and subset simulation is proposed. • Kriging is constructed based on exploration and exploitation of failure region. • Error measure functions are defined to quantify Kriging metamodel error. • The proposed method can handle problems with small failure probabilities. • Results of seven examples verify the accuracy and efficiency of proposed method. |
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• A new reliability method combining Kriging and subset simulation is proposed. • Kriging is constructed based on exploration and exploitation of failure region. • Error measure functions are defined to quantify Kriging metamodel error. • The proposed method can handle problems with small failure probabilities. • Results of seven examples verify the accuracy and efficiency of proposed method. |
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